exponential_moving_average

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that EMA 'gives more weight to recent observations', which is useful context about the algorithm's behavior. However, it doesn't address important aspects like numerical stability, handling of edge cases (e.g., small datasets), performance characteristics, or what the output represents. For a computational tool with no annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise - a single sentence followed by domain/category tags. It's front-loaded with the core purpose. The domain/category tags could be considered slightly extraneous but don't significantly impact conciseness. Every element serves a purpose, though more parameter guidance would improve completeness without harming conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given a 3-parameter computational tool with 0% schema description coverage and no output schema, the description is incomplete. It identifies the tool as an EMA calculator but doesn't explain parameter meanings, algorithm details, or expected output format. The domain/category tags provide some context but don't compensate for the lack of operational guidance needed to use this tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for undocumented parameters. The description mentions 'EMA' but doesn't explain what the three parameters (data, alpha, initial) represent or how they interact. While 'EMA' implies a timeseries input, no guidance is given about alpha's role as the smoothing factor or initial's purpose as the starting value. The description adds minimal value beyond the parameter names visible in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Compute Exponential Moving Average (EMA) - gives more weight to recent observations'. It specifies the verb ('Compute'), resource ('Exponential Moving Average'), and a key behavioral characteristic (weighting). However, it doesn't differentiate from sibling tools like 'simple_moving_average' or 'weighted_moving_average' beyond mentioning 'EMA' specifically.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal usage guidance through domain/category tags ('Domain: timeseries, Category: analysis'), which implies context but doesn't explicitly state when to use this tool versus alternatives. No specific when/when-not instructions or named alternatives are provided, leaving the agent to infer appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.